articleIEEE Transactions on Medical ImagingMay 22, 2020Closed access

Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images

Inception Institute of Artificial Intelligence · Wuhan University · +1 more institution

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Abstract

Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to face an existential health crisis. Automated detection of lung infections from computed tomography (CT) images offers a great potential to augment the traditional healthcare strategy for tackling COVID-19. However, segmenting infected regions from CT slices faces several challenges, including high variation in infection characteristics, and low intensity contrast between infections and normal tissues. Further, collecting a large amount of data is impractical within a short time period, inhibiting the training of a deep model. To address these challenges, a novel COVID-19 Lung Infection Segmentation Deep Network (Inf-Net) is…

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Authors

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Topics & keywords

Keywords
  • Coronavirus disease 2019 (COVID-19)
  • Artificial intelligence
  • Computer science
  • Segmentation
  • Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
  • Contrast (vision)
  • Economic shortage
  • Deep learning
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